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import openai
import gradio
import pandas as pd
from datetime import datetime
import gspread
from google.oauth2.service_account import Credentials
import requests
import json
import os
openai.api_key = os.getenv("API_SECRET")
records = []
credentials = Credentials.from_service_account_file("credentials.json", scopes=["https://www.googleapis.com/auth/spreadsheets"])
client = gspread.authorize(credentials)
sheet = client.open_by_url("https://docs.google.com/spreadsheets/d/1aZibKvwrvOB-xx_PSp2YFyuaycHyVkJZW_unC21VUbA/edit?usp=sharing").sheet1
def get_user_ip():
try:
response = requests.get("https://api.ipify.org?format=json")
data = json.loads(response.text)
return data["ip"]
except:
return None
def ContractDraftGPT(user_input, user_name, user_email, user_agent, is_fintech_startup, region):
messages = []
if not user_name:
return "Please enter your name."
user_message = f"{user_input} [USER_IDENTITY: {user_name}]"
messages.append({"role": "user", "content": user_message})
messages.append({"role": "system", "content": "You are a professional and experienced UK Lawyer who is drafting a legal document, a contract for your client base don his requirement. Make sure to mention and point precise legal rules, act of parliament (please insert which section of which article of which law, be precise when you refer to act of parliament), case law, and any pieces of secondary legislation. UK legislation."})
response = openai.ChatCompletion.create(
model="gpt-4",
messages=messages
)
ContractGPT_reply = response["choices"][0]["message"]["content"]
messages.append({"role": "assistant", "content": ContractGPT_reply})
# Record keeping
timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
ip_address = get_user_ip()
device_type = get_device_type(user_agent)
session_duration = "" # Calculate session duration
features_used = "" # Track features used
num_queries = "" # Count number of queries
num_documents_created = "" # Count number of documents created
clickstream_data = "" # Track clickstream data
interaction_patterns = "" # Track user interface interaction patterns
success_of_advice = "" # Measure success of advice
user_satisfaction_rate = "" # Measure user satisfaction rate
user_location = "" # Capture user location
industry_or_profession = "" # Capture user industry or profession
record = {
"Timestamp": timestamp,
"User Input": user_input,
"User Identity": user_name,
"User Email": user_email,
"IP Address": ip_address,
"Device Type": device_type,
"Session Duration": session_duration,
"Features Used": features_used,
"Number of Queries": num_queries,
"Number of Documents Created": num_documents_created,
"Clickstream Data": clickstream_data,
"Interaction Patterns": interaction_patterns,
"Success of Advice": success_of_advice,
"User Satisfaction Rate": user_satisfaction_rate,
"User Location": user_location,
"Industry or Profession": industry_or_profession,
"Contract Draft": ContractGPT_reply
}
records.append(record)
# Update Google Sheet
row_values = [
timestamp, user_input, user_name, user_email, ip_address, device_type, session_duration,
features_used, num_queries, num_documents_created, clickstream_data, interaction_patterns,
success_of_advice, user_satisfaction_rate, user_location, industry_or_profession, ContractGPT_reply
]
sheet.append_row(row_values)
return ContractGPT_reply
def get_device_type(user_agent):
if user_agent and "mobile" in user_agent.lower():
return "Mobile"
elif user_agent and "tablet" in user_agent.lower():
return "Tablet"
else:
return "Desktop"
def launch_interface():
inputs = [
gradio.inputs.Textbox(label="User Input", placeholder="Provide details for contract draft..."),
gradio.inputs.Textbox(label="Your Name", placeholder="Enter your name"),
gradio.inputs.Textbox(label="Your Email", placeholder="Enter your email"),
gradio.inputs.Radio(label="Are you a fintech startup?", choices=["Yes", "No"]),
gradio.inputs.Radio(label="Select your region:", choices=["England", "Scotland", "Wales", "Northern Ireland"])
]
outputs = gradio.outputs.Textbox(label="Contract Draft")
interface = gradio.Interface(fn=ContractDraftGPT, inputs=inputs, outputs=outputs, title="", description="")
interface.launch()
if __name__ == "__main__":
launch_interface()
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